Survey data on young people and education

Pierre Walthéry

UK Data Service

January 2026

The UK Data Service

Who we are

  • Five partner universities

    • UK Data Archive, University of Essex (lead partner)
    • Cathie Marsh Institute, University of Manchester
    • Jisc, University of Manchester
    • EDINA, University of Edinburgh
    • University College London
  • 100+ staff

  • Exists as UKDS since 2012 (as UKDA 1967)

  • National data since 2003

What we do

  • The main single point of access for UK social science data
  • Secondary data collection, curation and access
  • Training and user support
  • Communication and user engagement
  • Impact
  • … Key part of the UK social science research infrastructure, funded by the UKRI/ESRC

Our data…

  • UK social survey microdata:

    • Cross-sectional: large government and academic surveys
    • Longitudinal: major studies following people over time
  • Multinational data: survey data, aggregate databases

  • Census tables and individual data – current and historical

  • Business microdata and administrative data

  • Qualitative data: multimedia files and interview transcripts

Our training

  1. Webinars and online workshops
  2. User Conferences: Four main user conferences each year
  3. Drop-in sessions: Survey, Computational Social Science and SecureLab
  4. Online learning materials: find key resources on our Learning Hub
  5. Helpdesk for individual data queries
  6. Check out our YouTube channel

Key datasets for analysing young people and education

What do we mean by ‘data’ (1)

  • Individual vs aggregated
  • Nature of data: survey vs other source: devices, administrative records, etc.
  • About organisations (ie schools) vs people
  • From organisations and young people
  • One off studies vs series
  • Photography (ie cross-sectional) vs video (longitudinal)
  • Our focus today: individual survey microdata

What do we mean by ‘data’ (2)

  • Questions asked to people

    • About objective characteristics ie height, weight, age

    • About views and attitude:

      • Attitudes and opinions on crime, gender change
      • Validated instruments (ie mental health)
  • External measurement (biosample, genetic, cortisol levels)

  • Smart data (from devices ex accelerometer, energy meter)

  • Linked administrative records - more on this later

Major studies

At a glance …

  • (Birth) cohort studies
  • Understanding Society
  • Census
  • Linked data
  • A few repeated cross-sectional studies

Birth cohort studies

  • Follow a sample of individuals from birth until death
  • People born during during the same specific period of time in 1958(NCDS), 1970(BCS), 2000 (MCS), 2026 (Generation New Area)
  • Wide range of measurements, including education and health
  • Within and between cohort analysis
  • Managed by the Centre for Longitudinal Studies (UCL)

The Cohort Studies at the CLS

Screenshot from Cohort page on the Center for Longitudinal Studies website

Millennium Cohort Study (MCS)

  • ~ 19K children (born between June 2001 and Jan 2003)
  • 8 sweeps: age 9 months then 3, 5, 7, 11, 14, 17, 23
  • Parent and child interviews
  • Education, skills, health, truancy, cognitive ability…
  • Biological measurements
  • … Socio-economic and demographic characteristics
  • Data available at the UK Data Service here

Example: Kandola et al (2022)

  • Screen-based sedentary behaviour and depression

    • Is a sedentary lifestyle alongside screen and device usage, associated with depression?
    • Does physical activity make a difference?
  • 11,341 teenagers from the Millennium Cohort Study

  • The main outcome was depressive symptoms at age 14

    • A measured by the Moods and Feelings questionnaire
  • Against frequency of video game, social media, and internet use (age 11).

  • Impact of self-reported physical activity

Results

Screenshot from Table 2 from Kandola et al (2022)

  • IRR: likelihood of depression (\(<1=\)less likely, \(>1=\)more likely)

Conclusions

  • More frequent gaming at age 11 associated with a lower risk of depressive symptoms at age 14 for boys but not girls.
  • More frequent social media use at 11 associated with a higher risk of depressive symptoms in girls but not boys.
  • More frequent video game use was consistently associated with fewer depressive symptoms for boys with low physical activity, but not those with high physical activity

Next Steps

Understanding Society logo

  • 16,000 people born in 1989-90 followed from age 13-14
  • Annual sweeps between ages 14-20, then 25 and 32
  • Oversampling of ethnic minorities and deprived schools
  • Covers educational attainment and aspirations, health and well-being, and social attitudes
  • Linked administrative data available
  • Transitions from secondary to post-16 and higher education, family formation, housing, and early labour market entry
  • Available at the UK Data Service

Next Steps on the CLS website

Screenshot from Next Steps landing page

Growing Up in Scotland

Growing Up in Scotland logo

  • Large-scale, Scottish cohort study (Website)
  • Cohort 1:
    • A sample of children born in 2005-6
    • 11 yearly sweeps. Most recent is Sweep 11 (Age 17-18)
    • 5,217 children at Sweep 1 —> 2,469 at sweep 11
  • Cohort 2
    • a sample of children aged around 10 months in 2011.
    • 3 sweeps, most recentis Sweep 3 (Age 5 )
    • 6,127 at Sweep 1 —> 4,434 at Sweep 5
  • Growing up in Scotland Series at the UK Data Service

GuS Data and variables

  • Mental health: depression, Strengths and Difficulties Questionnaire)

  • Diet and sleep; Alcohol consumption, smoking, drug use

  • Anti-social behaviour and offending

  • Parent physical and mental health

  • Linked data

    • Sweep 11 school attainment records - using Scottish Candidate Numbers
    • Sweep 8 Recorded physical activity data

Understanding Society

Understanding Society logo

  • Largest longitudinal study of the UK population

  • 40K households, 100K individuals initially (2009)

  • 17 waves so far: 2009-23. Includes BHPS data 1991-2009

  • Ethnic minority boost samples, innovation panel

  • Very wide range of topics covered:

    • Employment, income, benefits, savings, debt, and assets
    • Health, well-being, and health behaviour
    • Housing, housing costs, and dwelling characteristics

Screenshot from the 'Understanding Children and teenagewrs in the UK' page on the Understanding Society website

Screenshot from Young People page fomr the Understanding Society website

Young people in Understanding Society

  • Youth (ie 10-15yo) self-completion questionnaire
  • Usage of smarphone and devices
  • Online vs in person socialising
  • Usage of apps
  • Family support, athmosphere and trust
  • Strength and Difficulties questionnaire; self-image
  • View about education; schoolwork and bullying

Young people and mental health (1)

Parra-Mujica, Johnson et al (2023)

  • Positive association between health for the 16 to 24 and:

    • differences in household income
    • short-term income changes are significant,
  • Microsimulation shows that respondents on lower income would benefit the most from increases in their income,

  • Focusing on the poorest risks neglecting other vulnerable subgroups, ie young workers and single youth

Young people and mental health (2)

Probability of scoring SF-12 MCS ≤45.6 indicating clinical depressive disorder by net equivalised household income quintiles.

Line plot of the probability of scoring SF-12 MCS ≤45.6 indicating clinical depressive disorder by net equivalised household income quintiles.

Linked administrative datasets

  • Records produced when a survey respondent interacts a government organisation

    • hospitalisation, sitting an exam, becoming an employee
  • Can be merged with survey data…

    • Where prior consent was obtained from respondents
  • Entails more stringent conditions of access (Secure access)

  • Early days, especially for everyday users but expanding area

Linked data examples

  • Understanding Society:
    • Scottish Education Data 2007-2018
    • National Pupil Database (England)
  • Millennium Cohort Study
    • Distances to English Grammar Schools, 2012
    • Distances to Current, 1st, 2nd, and 3rd Choice Schools
  • Next Steps:
    • Student Loans Company Records 2007-202
    • Individualised Learner Records

Census records

  • Fine grained socio-demographic population estimates

  • By age group:

    • Deprivation
    • Economic activity
    • Educational status
    • Ethnicity
    • Disability
  • Typical application: population estimates for small areas

Residents aged 0-24 as a % of the population by LSOAs , 2021

Map  of Residents aged 0 to 24 as a percentage of the total all age  population Lower Super Output Areas,2021.

Source

Is this everything?

Young People and Gambling Survey

  • Attitudes towards and participation in different types of gambling activities

    • Legal and age restricted gambling
  • Data controller: Gambling Commission.

  • 3,666 pupils aged 11 to 17 yo (school years 7 to 12 (S1 to S6 in Scotland

  • You can find it here

Children’s People and Nature Survey

  • Population: young people aged 8-15 yo
  • Experience of and views about the natural environment
  • Two waves: one in term time, one in holiday time.
  • Sample size: about 4,000 per year, 2,000 per wave
  • Time spent outside
  • Quality of outdoor spaces
  • Opportunities and barriers to spending time outside
  • Environmental concerns and action
  • Connection with nature
  • Countryside code

Smoking, Drinking and Drug Use among Young People

  • About 17,000 young people aged 11 to 15 (2023) in England
  • Focus on prevalence of smoking, drinking and drug taking
    • types of substance taken;
    • how often pupils smoke, drink and take drugs
    • where susbtance are obtained
    • pupils’ attitudes to these behaviours
  • Produced by NHS England.
  • Study page on the UK Data Service website

Qualitative & deposited research data

  • No qualitative equivalent to the major quantitative studies but…
  • ESRC grantholders are required to deposit their data
  • A growing treasure trove of qualitative (and quantitative ) research data on various topics, including young people
  • Often freely accessible via ReShare on the UKDS website, data owner authorisation is sometimes required

Finding data

The main UKDS data catalogue page

Screenshot of the main catalogue search page  on the UKDS website

Catalogue search results for ‘young people’ - Studies tab

Screenshot of  catalogue search results for 'Young people' on the UKDS website

Catalogue search results for ‘young people’ - ReShare tab

Screenshot of the Reshare results of a UKDS catalogue search for Young People

The Youth Theme page of the UK Data Service catalogue

Screenshot of the Youth theme page on the UKDS website

QualiBank catalogue search results for ‘young people’

Screenshot of s search result for 'young people'in the Qualibank

How to access the data

Levels of access

A slide showwing the four levels of data access at the UK Data Service

  • The lesser the conditions for accesssing the data, the fewer the details included
  • Open data includes fewer personal information; controlled data significantly more
  • Safeguarded data strikes a compromise between accessibility and level of detail

How to access safeguarded data

  • Register with the UK Data Service

  • Create a project (‘non commercial’, ‘commercial’, ‘teaching’)

  • Search, find and order the data

  • Add it to your project

  • Download it…

  • Et voilà.

  • The steps to follow are detailed on our website

Other levels of access

  • Open data: can be downloaded without registration

  • ReShare data (ie deposited) data: conditions will depend on the data owner; most of the time freely downloadable

  • Controlled data:

    • Register
    • Provide a detailed description of your project
    • Apply for Safe Researcher certification
    • Follow the Safe Researcher training
    • Access the data via the SecureLab - ie secure VPN from an institutional computer

Essential questions to ask yourself

  • Data quality
    • What was the phrasing of the question(s)?
    • What was the research question/funder of the research?
    • Is it representative, is the sample size large enough, what is the population of reference?
    • When was it collected?
    • Is the documentation – technical report available?
    • Are weights and survey design information provided?
  • Is a special application required in order to access the data?

Conclusion

Take aways

  • Wealth of data on young people and education
  • From surveys and beyond
  • Education and other relevant topics
  • Different ways of searching
  • Different levels of access

Thank you for your attention

Any questions: help@ukdataservice.ac.uk